TA job descriptions blocks 1 and 2, 2020-21

Read about the assignments you are required to handle as a teaching assistant in courses at the Department of Computer Science.

Apply for the open positions via this link to KU's jobportal


A teaching assistant writing on a blackboardThere are vacant TA-positions on the following courses (the courses not on the list is in the proccess of hiring): 


Computer Science

Advanced algorithms and data structures (AADS) i blok 1

Course organizer: Christian Wulff-Nilsen, koolooz@di.ku.dk

There are 2 x 2 hours of exercises per week. The norm is that you get 1.5 hours of preparation for each of these hours. 

In addition, the students will have 2 assignments to be handed in in groups that have to be passed, and this includes are re-handin. The TAs will correct/comment these assignments including hand-ions.  Each TA is expected to be responsible for about 15 groups.

It is expected that TAs help prepare instructions and assignments for exercise classes and the course page, to prepare and give exercise classes, participate in e-mail correspondance about TA tasks, help administer the course home page and participate in the forum at absalon.

Advanced Computer Systems (ACS) in block 2

Course organizer: Thomas Troels Hildebrandt, hilde@di.ku.dk

Being a TA for Advanced Computer Systems (ACS) involves primarily: (a) supporting students with the theory/programming assignments; (b) holding weekly TA exercise sessions; (c) grading assignments; (d) attending a small subset of the lectures to support in-lecture exercises; (e) helping with pre-grading of the exam assignment.

For activity (a) to work out, we typically ask new TAs to work a bit in advance of the course with the code base used for the assignments. This makes a dramatic difference on how much help you can offer to your fellow students during the course. Also, a large chunk of (b) is dedicated to Q&A on the assignments. So the advance investment you make into the code base reflects in higher quality and lower work during the teaching weeks.

Activity (d) is implemented as a rotation among the TAs, so each TA only gets to be present in lectures in a couple of the weeks of teaching.

Activity (e) is about the same effort (or lower) that a TA would put into grading one of the assignments. But it must happen in the week after the exam.

The regular teaching weeks aside, the TAs are expected to help out well in advance of the course and in the week after the exam week. During regular teaching weeks, I TAs are expected to devote 10-15 hours to TA tasks and outside regular teaching weeks 1-5 hours.   TAs are expected to prepare for, and hold exercise sessions, come to weekly TA meetings, participate in email correspondence about TA tasks, participate in the forum on the course website and help students outside of regular hours.

In connection with admitting students to the exam, TAs are expected to help with correcting and approving homework assignments. In connection with holding the exam help will be needed with correcting and approving homework assignments.

Advanced programming (AP) in block 1

Course organizer: Ken Friis Larsen, kflarsen@di.ku.dk

The major work of the TA work consist of preparing for, and hold weekly lab/exercise sessions; and giving feedback on the weekly hand-in of assignments. This year the hope is to use the OnlineTA system, thus there will also be some work preparing assignments for this system, and help running during the course. But hopefully OnlineTA will lessen the burden of menial correction of student hand-ins.

The languages used in AP are: Haskell, Prolog, and Erlang.

The regular teaching weeks aside, the TAs are expected to help out well in advance of the course, in the week after the exam week and several weeks after the exam week. During regular teaching weeks, TAs are expected to devote 10-15 hours to TA tasks and outside regular teaching weeks 10-15 hours to TA tasks. TAs are expected to help design the tutorials for use in exercise sessions and on the course website, prepare for, and hold exercise sessions, come to weekly TA meetings, participate in email correspondence about TA tasks, participate in the forum on the course website and help students outside of regular hours and help manage the OnlineTA exercise hoped to be used during the course.

In connection with admitting students to the exam, TAs are expected to help with preparing the homework assignments, dry-running the homework assignments and correcting and approving homework assignments. In connection with holding the exam, TAs should help with dry-running the exam and preliminarily correcting the exam. In connection with holding the reexam perhaps TAs can help dry-running the reexam.

Advanced Topics in Natural Language Processing (ATNLP)

Course organiser: Desmond Elliott, de@di.ku.dk

Description:

The TA is expected to prepare for, and run weekly Lab sessions for the course, attend weekly TA meetings and participate in email correspondence about TA tasks, participate in the Absalon discussion forums and respond to student questions in a timely manner.

The TA is also expected to contribute to assessing students in the in-class paper presentations, the oral group presentations, and the final written report.

Advanced Topics in Machine learning (ATML) in block 2

Course organizer: Yevgeny Seldin, seldin@di.ku.dk.

The tasks of the TAs include:

  • Advising students in the exercise classes (e.g., answering questions regarding the material presented in the lecture). There is one three hour exercise class per week.
  • Presenting reference solutions in the exercise classes.
  • Helping with correcting weekly home assignments.
  • Participating in a weekly TA meeting (about 1 hour).

Overall workload is about 15 hours / week throughout the block.

TAs are required to have very good command of machine learning, as demonstrated for example by a good grade in "Advanced Topics in Machine Learning" course. TAs are also required to have strong math skills (linear algebra, analysis, and probability theory).

For more details about the TA job, please, contact the course organizer Yevgeny Seldin, seldin@di.ku.dk.

Big Data Systems (BDS) in block 2

Course organizer: Yongluan Zhou zhou@di.ku.dk

The goal of this course is to give the participants an understanding of the technologies in computer systems for Big Data analysis and management. It covers both traditional methods used in data warehouses and parallel database systems, real-time stream processing systems, transactional database systems, as well as modern technologies of cloud computing and massively parallel data analysis platforms.  

The following main topics are contained in the course:

  • Data warehouses;
  • Parallel database systems;
  • Massively parallel data analysis;
  • Fast stream processing systems;
  • Big graph processing;
  • High-throughput transaction processing;

Computersystemer (CompSys) in block 1 og 2

Kursusansvarlig: Michael Kirkedal Thomsen, m.kirkedal@di.ku.dk , Telefon: 35336154

Computer Systems runs over the entire first semester. The main task of the TA work consists of preparing for and holding weekly lab/exercise sessions and grading and giving feedback on the handed-in assignments.

Furthermore, the TAs are expected to help out in advance of and during the course with testing the curriculum, forming of exercises, assignments and tutorials as well as other miscellaneous tasks.

TA tasks include:

  • Help design and dry-run exercises and assignments.
  • Prepare for and hold lab sessions.
  • Grade and give feedback to hand-in of assignments.
  • Attend weekly meetings.
  • Participate in e-mail correspondence about TA tasks.
  • Be active (and helpful) on the course website forums.
  • Help students outside of regular working hours.

Cloud-baserede sundhedsapps

Kursusansvarlig: Thomas Troels Hildebrandt, hilde@di.ku.dk 

Som instruktor på bachelorkurset Udvikling af cloud-baserede sundheds-apps forventes det, at du er god til at programmere og har erfaring med/lyst til at lære at udvikle mobile applikationer til Android/IOS. Det er ikke et krav, at du har instruktor- eller undervisningserfaring, men vi forventer at du er en åben og engageret person. Kurset ligger i forlængelse af to tidligere programmeringskurser, så de studerende har lidt erfaring med programmering, når de starter på kurset. Vi bestræber os på at være fleksible mht. planlægning af arbejdsbyrden i forhold til dit studie og forventer, at du vil kunne være fuldtidsstuderende samtidigt med dit instruktorjob.

Instruktoropgaver:

  • deltage i instruktormøder
  • give feedback på opgaver/øvelser
  • afholde ugentligt øvelsestimer
  • besvare spørgsmål fra studerende online

Disket Matematik og Algoritmer" (DMA) i blok 1 og 2

Kursusansvarlig: Mikkel Abrahamsen, miab@di.ku.dk 

Disket Matematik og Algoritmer" (DMA) vil give de studerende en introduktion til diskret matematik, algoritmer og datastrukturer. Kurset er på første år og løber over 2 blokke (blok 1 og blok 2). De matematiske dele ligner delvist det gamle "Diskrete matematiske Strukturer" (DiMS) kursus. De datalogiske dele er indeholdt i det gamle "Algoritmer og Datastrukturer" (AD) kursus, men mindre omfattende. De studerende vil se simple eksempler på anvendelse af diskret matematik til konkrete algoritmer. Vi forventer, at instruktorerne til DMA har taget kurser i diskret matematik og indledende algoritmik, f.eks. DMA eller DiMS og AD.

Kurset vil blive opbygget omkring forelæsninger og øvelsestimer. Eksamen består en række hjemmeopgaver. Instruktorernes primære opgaver vil være afholdelse af øvelsestimer inkl. forberedelse samt retning af hjemmeopgaver. Derudover kan deltagelse i lektiecafeer og lignende også være med i instruktoraterne.

Det er vores mål at være fleksible i forhold til hvor mange timer, I som instruktorer bruger hver uge, så det i så høj grad som muligt passer ind i jeres studier. Afhængig af hvor mange timer I ønsker, kan vi f.eks. justere mængden af rettearbejde. Vi foretrækker instruktorer, som kan undervise i både blok 1 og 2.

Interesserede er meget velkomne til at kontakte Stefan Sommer (kursusansvarlig).

High Performance programmering og systemer (HPPS) in block 2

Kursusansvarlig: Stefan Horst Sommer, sommer@di.ku.dk

Instruktoropgaver:

  • deltage i instruktormøder
  • give feedback på opgaver/øvelser
  • afholde ugentligt øvelsestimer
  • besvare spørgsmål fra studerende online

Se eventuelt kursusbeskrivelsen på kurser.ku.dk

Introduktion til computergrafik (Grafik) i blok 2

Kursusansvarlig: Kenny Erleben, kenny@di.ku.dk

The TA must have passed the course “Introduction to computer graphics” or equivalent and should be a confident C++ programmer.

The TAs tasks are:

  • Lead the exercise sessions and help students solve the exercises.
  • Give feedback on students solutions to the exercises.
  • Answer course related questions in the discussion board in Absalon.

Se kursusbeskrivelsen her

Introduktion til Machine Learning (MaLeIntro) blok 1-2

Kursusansvarlig: Stefan Horst Sommer, sommer@di.ku.dk

Instruktoropgaver:

  • deltage i instruktormøder
  • give feedback på opgaver/øvelser
  • afholde ugentligt øvelsestimer
  • besvare spørgsmål fra studerende online

Se eventuelt kursusbeskrivelsen på kurser.ku.dk

IT-projektledelse (ITP) i blok 1

Kursusansvarlig: Jørgen Bansler, bansler@di.ku.dk

1) Afholdelse af øvelser i ugerne 36-41 og 43

  • Svare på spørgsmål vedr. pensum
  • Opsummere tværgående problemstillinger fra løsningen af forrige uges opgave
  • Vejlede og hjælpe med løsning af indeværende uges opgave
  • samt hvad I og de studerende ellers finder relevant.

Øvelserne afholdes torsdag eftermiddag (eller tirsdag formiddag) i blok 1.

2) Rette ugeopgaver, formentlig efter følgende proces:

  1. Besvarelserne ligger i Absalon mandage kl. 18.
  2. Senest tirsdag kl. 18 sender I mig jeres bedømmelser af de besvarelser, som I måtte være usikre på, hvordan I skal bedømme (herunder om der skal genafleveres) – typisk 2-3 besvarelser.
  3. Senest onsdag kl. 10 får I feedback fra mig på jeres udvalgte bedømmelser, med henblik på at sikre en fælles måde at bedømme besvarelserne på.
  4. På instruktormødet (typisk via skype onsdag aften) drøfter vi tværgående forhold vedr. bedømmelserne.
  5. Så vidt muligt inden øvelserne torsdag giver I en kort skriftlig feedback på Absalon til hver enkelt gruppe, der har lavet en besvarelse.
  6. På øvelserne samler I de ting op, som mange har haft problemer med i besvarelserne, og fortæller, hvordan det kunne have løst. Vis gerne en prototypisk god besvarelse frem, og læg den på Absalon.

Afhængig af den endelige skemaplanlægning kan der ske justeringer af tidspunkterne ovenfor. 

3) Deltage i instruktormøderne

Udover rettelsen af forrige uges opgavebesvarelser drøfter vi her kriterier for rettelse af de kommende ugeopgaver, samt problemstillinger (fx vedr. forståelse af pensum), der har vist sig på øvelserne.

Sidste år foregik de fleste af instruktormøderne, bortset fra indledende møde og møde før eksamensopgavevurderingen via skype onsdag aftener kl 19-20.

4) Lave en forhåndsvurdering af de studerendes eksamensopgavebesvarelser, ud fra en skabelon som jeg laver.

Det er vigtigt at I afsætter god tid hertil i uge 44.

IT-sikkerhed (ITS) in block 1

Course organizer: Michael Kirkedal Thomsen, m.kirkedal@di.ku.dk , Telefon: 35336154

The lion’s share of the TA work consists of preparing for and holding weekly lab/exercise sessions and grading and giving feedback on the weekly hand-in of assignments.

Furthermore the TAs are expected in limited amounts to help out in advance of and during the course with planning of the curriculum, forming of exercises, assignments and tutorials as well as other miscellaneous tasks.

TA tasks include:

  • Help design and dry-run exercises and assignments.
  • Prepare for and hold lab sessions.
  • Grade and give feedback to weekly hand-in of assignments.
  • Attend possible weekly meetings.
  • Participate in e-mail correspondence about TA tasks.
  • Be active (and helpful) on the course website forums.
  • Help students outside of regular working hours.

Logic in Computer Science (LICS) in block 2

Course organizer: Robin Kaarsgaard, robin@di.ku.dk

TA tasks:

  • Commenting of obligatory exercises
  • weekly excercise classes
  • fielding questions on class forum
  • individual ad-hoc advising/follow-up.

See the course description.

Machine learning (ML) in block 2

Course organiser: Yevgeny Seldin, seldin@di.ku.dk.

The tasks of the TAs include:

  • Advising students in the exercise classes (e.g., answering questions regarding the material presented in the lecture). There is one three hour exercise class per week.
  • Presenting reference solutions in the exercise classes.
  • Correcting weekly home assignments.
  • Participating in a weekly TA meeting (about 1 hour).

Overall workload is about 15 hours / week throughout the block.

TAs are required to have good command of machine learning, as demonstrated for example by a good grade in „Machine Learning“ and/or "Advanced Topics in Machine Learning" courses. TAs are also required to have reasonable math skills (basic linear algebra, analysis, and probability theory should not be scary for you).

You can find a more detailed description of tasks and their time estimates at https://docs.google.com/document/d/1YCLTnLDurJwkW7GebfIdNsuAzdNUC907d_dryKF3pP8/

We are also looking for one Master TA. Master TA will be responsible for running the TA team. For this job we are looking for a highly organized person that is punctual, responsible, and likes organizing things. If you would like to be considered for the role of Master TA, please, state it in your application.

For more details about the TA job, please, contact the course organizer Yevgeny Seldin, seldin@di.ku.dk.

Makroøkonomi A (MakØkA) i blok 2

Kursusansvarlig: Martin Elsman, mael@di.ku.dk

Instruktoropgaver:

  • deltage i instruktormøder
  • give feedback på opgaver/øvelser
  • afholde ugentligt øvelsestimer
  • besvare spørgsmål fra studerende online

Se eventuelt kursusbeskrivelsen på kurser.ku.dk

Matematisk analyse og statistik i datalogi (MASD) i blok 1

Kontakt: Pawel Winter, pawl@di.ku.dk, TA tasks: Holding weekly exercise classes, correcting assignments, pre-testing of assignments, participation in weekly TA meetings. As a starting point, the workload is about 10-15 hours per week, but we are willing to be flexible in adapting to the TAs time schedules.

Modelling and analysis of data (MAD) in block 2

Kontakt: Fabian Cristian Gieseke, fabian.gieseke@di.ku.dk

TA tasks: Holding weekly exercise classes, correcting assignments, pre-testing of assignments, participation in weekly TA meetings. As a starting point, the workload is about 15 hours a week, but we are willing to be flexible in adapting to the TAs time schedules.

Natural Language Processing (NLP) in block 1

Course organiser: Isabelle Augenstein, augenstein@di.ku.dk

TA tasks: The TA is expected to prepare for, and hold exercise sessions, come to weekly TA meetings, participate in email correspondence about TA tasks, participate in the forum on the course website and help students outside of regular hours. In connection with admitting students to the exam, the TA is expected to help with dry-running the homework assignments, correcting and approving homework assignments and preparing guiding solutions for homework assignments. In connection with holding the exam, the TAs is expected to help with dry-running the exam and preliminarily correcting the exam.

Numeriske Metoder (NuMe) blok 1

Kursusansvarlig: Martin Elsman, mael@di.ku.dk

Instruktoropgaver:

  • deltage i instruktormøder
  • give feedback på opgaver/øvelser
  • afholde ugentligt øvelsestimer
  • besvare spørgsmål fra studerende online

Se eventuelt kursusbeskrivelsen på kurser.ku.dk

Programmering og problemløsning (PoP) i blok 1 og 2

Kursusansvarlig: Jon Sporring, sporring@di.ku.dk

Programmering og problemløsning (PoP) underviser i programmering med fokus på de 3 paradigmer, imperativ, funktionel og objektorienteret, og sproget er F#. Vi bruger mono-platformen, kommandolinjen, emacs, og latex. Undervisningsformen lægger vægt på programmering som et håndværk og rapportskrivning. Kurset ligger i skema A.

Som instruktor på PoP skal du:

  • ugentligt varetage 3x2 timers øvelsestimer,  
  • ugentligt deltage i 1 times instruktormøde typisk mandage eller tirsdage i frokostpausen,  
  • ugentligt varetage evaluering af de studerendes løbende afleveringer (12-14 i alt i løbet af kurset) og give feedback til de studerende  
  • løbende deltage i dialog med de studerende via Absalon, e-mail, etc.  
  • deltage som lektiehjælper på lektiecafeen efter en turnusordning, typisk 4 gange i alt.  
  • deltage i en halvdags forberedende workshop i ugen op til kursusstart  
  • evt. deltage i forberedelsen af relevante studerende til reeksamen mellem blok 3 og 4.

Som instruktor på PoP forventes det, at du er god til at programmere og har grundig kendskab til F#, men det forventes ikke, at du ved alt. Det er heller ikke et krav, at du har instruktor- eller undervisningserfaring, men vi forventer at du er en åben og engageret person, og vi vil i løbet af kurset arbejde med din rolle som instruktor i forhold til de andre undervisningsaktiviteter, som foregår på kurset og på 1. år på datalogi. Undervisning på PoP og i det hele taget på 1. år på datalogiuddannelsen er en hold opgave, og vi lægger vægt på at hele instruktorholdet fungerer godt sammen, og at det er en lærerig og givende oplevelse for alle. Vi vil bestræbe os på at være fleksible mht. planlægning af arbejdsbyrden i forhold til dit studium og forventer, at du vil kunne være fuldtidsstuderende samtidigt med dit instruktorjob.

Kurset bliver kørt et tæt parløb med parallelkurset, Diskret Matematik og Algoritmer (DMA).

Programming Massively Parallel Hardware (PMPH) in block 1

Course organizer: Cosmin Oancea, cosmin.oancea@di.ku.dk

The TA will mainly be in charge of marking the weekly assignments and moderating the Absalon discussion forum. See the course description.

Python Programming for Data Science in block 1

Course organiser: Wouter Krogh Boomsma, wb@di.ku.dk & Thomas Wim Hamelryck, thamelry@bio.ku.dk

Python Programming for Data Science (previously called Linux and Python Programming) is an introductory programming course. It is primarily targeted at Bioinformatics students but typically attracts students broadly from the Science Faculty. The goal of the course to teach students to write short, well-structured programs in Python, with a focus on preprocessing data for downstream data analysis tasks. The course is in Schedule Group B.

As a TA in this course, you are expected to:

  • Help out with interactive teaching sessions. The 2x3 hour weekly lecture-sessions consist of a mix of classic lectures and exercises, and for each session, two TAs are present to help with these exercises.
  • Take turns hosting the 2x2 hour weekly exercise sessions.
  • Participate in online discussions with the students on Absalon, email etc.
  • Helping out with marking exercises

TAs in this course are expected to be confident Python programmers. You don't need to know everything, but you should be open to interacting with the students and try to give them a positive experience with learning their first programming language.

Virtual Reality (VR) in block 2

Course organiser: Joanna Bergström, joanna@di.ku.dk

Course Description

The aim of the course is to teach students to design and develop for virtual reality (VR). Participants will learn to develop for VR in a standard tool such as Unity, create interactions between avatar bodies and virtual objects, and design selection and manipulation techniques for VR. The course focuses both on the technical aspects of VR as well as on the human-centred aspects. These skills are needed to develop for headset-based VR, but also in developing for other headset-based technologies, such as augmented reality. Learning will happen through lectures and hands-on VR development exercises.

See more at https://kurser.ku.dk/course/ndab20008u/2020-2021

Responsibilities

The TAs are expected to take on the following responsibilities:

  • Help preparing programming assignments. 
  • Hold exercise classes on developing for VR and supervise project work of student groups during the regular weekly classes.
  • Help, discuss, and answer the students’ questions online on the course forums and website.
  • Participate in weekly TA meetings with the course coordinator.
  • Help giving feedback for, and grading hand-ins.

Requirements

The position as a TA for Virtual Reality requires proficiency with C# and experience with the Unity workflow. We will need 2 TAs for the course. The workload for each TA will be up to 135 hours in total (approximately 15 hours a week). This includes 3-4 hours of in-class assistance, weekly meeting of 1 hour, and assignment planning, online guidance of students, and hand-in evaluation tasks. 

Vision and Image Processing (VIP) in block 2

Course organizer: Søren I. Olsen, ingvor@di.ku.dk

TA tasks: Correction of 4 mandatory assignments and feedback. Weekly 2 hours help with assignments at class (7 weeks). One assignment is individual, the rest is in groups.

Visualisation (VIS)

Course organiser: Henning Pohl, henning@di.ku.dk

TA tasks:

  • attending TA-meetings
  • commenting of obligatory exercises
  • weekly excercise classes
  • answering questions on class forum
  • individual ad-hoc advising/follow-up

See the course description.

Økonometri A (ØkA) blok 1

Kursusansvarlig: Bertel Schjerning, bertel.schjerning@econ.ku.dk

Instruktoropgaver:

  • deltage i instruktormøder
  • give feedback på opgaver/øvelser
  • afholde ugentligt øvelsestimer
  • besvare spørgsmål fra studerende online

Se eventuelt kursusbeskrivelsen på kurser.ku.dk

Introduktion til økonomi (ØkINtro) blok 2

Kursusansvarlig: Morten Graugaard Olsen, mgo@econ.ku.dk

Instruktoropgaver:

  • deltage i instruktormøder
  • give feedback på opgaver/øvelser
  • afholde ugentligt øvelsestimer
  • besvare spørgsmål fra studerende online

Se eventuelt kursusbeskrivelsen på kurser.ku.dk

Kommunikation og it

KOMIT Empiriske undersøgelsesmetoder 2 og videnskabsteori block 1-2 (fall)

Course organiser: Irina Shklovski, ias@di.ku.dk

TA tasks:

  • attending TA-meetings
  • commenting on obligatory exercises
  • weekly excercise classes
  • answering questions in class forum

See the course description.

 

KOMIT Konceptudvikling og Innovation block 1-2 (fall)

Course organiser: Anne Mette Thorhauge, thorhaug@hum.ku.dk

TA tasks:

  • attending TA-meetings
  • commenting on obligatory exercises
  • weekly excercise classes
  • answering questions in class forum

See the course description.

KOMIT IT infrastructure in block 1-2 (fall)

Course organiser: Katarzyna Wac, wac@di.ku.dk

Description

There are 70-75 KomIT students organised in groups: A and B
Each week we teach 2 days: 2 x 2h / each class (A and B) / each day

The course is given by two professors: one from KomIT/HUM and one from DIKU.

The TA is expected to prepare for, and hold exercise sessions, be present at the weekly TA meetings (likely online), participate in email correspondence about TA tasks, participate in the forum on the course website and help students outside of regular hours. In connection with admitting students to the exam, the TA is expected to help with dry-running 4 obligatory homework assignments, preparing guiding solutions for homework assignments and then correcting and approving homework assignments (pass/fail level). In connection with holding the exam, the TAs is expected to help with dry-running the exam and preliminarily correcting the exam.

KOMIT Grundlæggende datalogi i blok 1 og 2

Kursusansvarlig: Jakob Grue Simonsen, simonsen@di.ku.dk

The main purpose is to run tutorials with students (twice a week, 2 hours each). The exercises are defined already, so the TA is expected to prepare herself/himself in advance of the tutorials. In addition, TAs are expected to assess the weekly assignments (pass/fail), of which students have to hand in 7 in the entire semester.

We will need 3 TAs for the course. During regular teaching weeks, the TAs is expected to devote 5-10 hours to TA tasks.

The TAs are expected to prepare for, and hold exercise sessions, come to weekly TA meetings, participate in the forum on the course website and help students outside of regular hours. In connection with admitting students to the exam, TAs are expected to help with correcting and approving homework assignments.

KOMIT Konceptudvikling og innovation i blok 1 og 2

Kursusansvarlig: Thomas Troels Hildebrandt, hilde@di.ku.dk

Kurset er baseret på projektarbejde i grupper, og instruktorer vil få tildelt grupper, de skal følge og vejlede løbende. Der vil være en række ‘teoretiske’ øvelser, hvor instruktorerne står for at hjælpe med at svar på opgaverne. Kurset følger semester struktur.