FLKM5000 Master's Thesis Course description

Arbeids- og undervisningsformene som benyttes er varierte og består av individuelle litteraturstudier, forelesning, gruppearbeid, caseoppgaver og praksisrelaterte arbeidsoppgaver.

Bacheloroppgaven ved yrkesfaglærerutdanningen innebærer å planlegge, gjennomføre og dokumentere en FoU-prosess knyttet til yrkesopplæring (med fleksibel vekt på utviklingsarbeid eller forskning) i skole og/eller arbeidsliv.

All the courses in the first year of the programme must be passed and all required coursework must be approved before the students can submit the master’s thesis and take the oral exam as the final assessment. This applies for students starting the programme until/including the academic year 2022-2023.

The following applies for students starting the programme in the academic year 2023-2024 and onwards:Students must have passed all of the courses in the first year of their study programme (FLKM4110, FLKM4210, FLKM4310/FLKM4320, and FLKM4410) before they can commence the course FLKM5000.

In very special cases and by application, partial deviation from these requirements may be considered.

Eksamen i emnet består av to deler:

Del 1: Bacheloroppgave, gruppe på 2-4 studenter, eventuelt individuelt, omfang 6600 ord +/- 10 % + vedlegg.

Del 2: Individuell muntlig presentasjon, Omfang: 30-45 minutter pr. kandidat. (15 min til presentasjon og inntil 30 minutter til oppklarende spørsmål). Individuell muntlig eksamen skal vise helhetlig yrkesfaglærerkompetanse.

Nærmere retningslinjer for eksamen i del 1 og del 2 gis av emneansvarlig

Ny og utsatt eksamen

• Ved sykdom arrangeres ny eksamen som ved ordinær eksamen. Dersom det ikke kan dannes grupper til del 1, gjennomføres den individuelt
• Ved karakteren F for ikke bestått, kan en omarbeidet versjon av bacheloroppgaven leveres til ny sensur inntil én gang, muntlig eksamen gjennomføres på nytt
• Studentens rettigheter og plikter ved ny/utsatt eksamen framgår av forskrift om studier og eksamen ved OsloMet
• Studenter er selv ansvarlige for å melde seg opp til eventuell ny/utsatt eksamen på Studentweb

Alle hjelpemidler tillatt

Del 1: Gradert skala fra A til E for bestått og F for ikke bestått, og teller 40 % av samlet karakter for emnet

Del 2: Gradert skala fra A til E for bestått og F for ikke bestått, og teller 60 % av samlet karakter for emnet

This course provides a broad introduction to Artificial Intelligence (AI), with methodologies and techniques that can be applied to different application domains. The course will balance theoretical approaches and practical tasks. Two broad AI areas will be covered, namely supervised and unsupervised methods. Among those, standard methods for regression, classification and clustering will be covered, e.g. support vector machines, nearest neighbor, decision tree, K-means, agglomerative and hierarchical clustering. An introduction to the usage of artificial neural networks and backpropagation algorithm will be provided.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and competence:

Knowledge

The student:

• has become familiar with key issues relating to innovation and entrepreneurship
• understands business processes and organisational structures in a start-up company
• has acquired a basic overview of financing and support possibilities for start-up companies
• has acquired insight into innovation processes and technological development from idea to prototype
• understand the role and importance of the UN's Sustainable Development Goals in the development of new technological solutions.

Skills

The student is capable of:

• developing a product or service from the idea, design and development stages through to implementation and evaluation of a prototype
• independently completing an IT project within the framework of a start-up company and mastering basic issues that characterise entrepreneurship processes
• communicating, in written and oral form, the technical and business-related issues of relevance to the theme of the project, including the project plan, project activities and results, to an audience that may or may not be technologically proficient
• developing new solutions that explicitly address one or several of the UN's Sustainable Development Goals

General competence

The student is capable of:

• using technical principles to solve one or more problems of relevance to the business sector
• defining a problem and proposing possible innovative solutions
• evaluating the importance of organisational dynamics and work relations in start-up companies

Supervision sessions with an external and/or internal supervisor. The students will work alone or in groups of two to five students on an IT project in a start-up company.

Projects are selected/distributed at the start of the semester. 

The following coursework is compulsory and must be approved before the student can take the exam:

• A project outline that describes how the group will organise their work on the project.
• A standard learning agreement must be entered into between the start-up company and the student(s), and this must be approved by the internal supervisor before the project can begin.
• Three meeting minutes from supervisory meetings during the project period.
• An oral mid-term presentation, individual or in groups (max 5 students), 10 minutes + 5 minutes Q&A.

The deadlines for submitting the project outline and minutes of the meetings will be presented in the teaching plan, which is made available at the beginning of the semester.