JB2220 Investigative journalist`s methods Course description

After completing the course, the student should have the following overall learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student has knowledge of

• how majority - minority relations in a historical, social and political perspective is related to the production of knowledge and power
• of how socioeconomic conditions, marginalization processes, racism and discrimination can impact quality of life and integration
• the importance of identity, language and cultural continuity for children and young people's development
• migration in a life-course and transgenerational perspective
• trauma, stress and adverse experiences related to forced migration and potential impact on mental health, social relations and the risk of developing mental health problems

Skills

The student can

• analyze structural, cultural and individual power relations and be able to apply this in anti-racist social work
• analyze and critically reflect on how cultural attitudes, values and behaviors can affect work with children and families in the welfare state.
• analyze conditions at the individual, group and societal level that may inhibit and promote health, development and social participation, for people with a history of migration, trauma and adverse experiences.

General competence

The student

• has gained an understanding of how cultural variation, migration histories and power relations have an impact on the needs and everyday lives of children, young people and families.
• has knowledge that stimulates reflection on the social and child welfare workers' positions of power both as representatives of public authorities and as representatives of a majority culture.

The teaching takes place with in-person attendance on campus. The teaching methods are lectures, plenary discussions, group work and own reflection. Students will also work on specific theoretical and methodological issues related to their own experiences and will be given an opportunity to discuss them.

Studenten skal etter å ha fullført emnet ha følgende totale læringsutbytte definert i kunnskap, ferdigheter og generell kompetanse:

Kunnskap

Studentene skal få kunnskap om

• Den undersøkende journalistikkens samfunnsrolle
• Ulike digitale verktøy for å hente inn, behandle og analysere relevante data
• Faktasjekk, kildekritikk, (digitalt) kildevern, innsynsrett, relevante lovverk og tilsvar/samtidig imøtegåelse i undersøkende journalistikk
• Hvordan man organiserer en frilansøkonomi og enkeltpersonfortak som undersøkende journalist

Ferdigheter

Studenten kan

• Gjøre kildekritiske vurderinger og utøve kildevern
• gjøre avanserte søk for å hente inn kompleks informasjon fra offentlige tilgjengelige databaser og registre
• skaffe seg innsyn og klage på avslag
• behandle informasjon systematisk, faktasjekke den og formidle den journalistisk i et klart og enkelt format

Generell kompetanse

Studenten kan

• reflektere over gravejournalistikkens samfunnsrolle i den norske velferdsstaten

Det legges opp til stor grad av studentaktiv læring. Undervisningen er organisert med forelesninger, seminarundervisning og praktiske øvelser i undersøkende metoder. Studentene skal løse både gruppeoppgaver og individuelle oppgaver.

Emnet har fire læringsmapper:

• Mappelevering 1: Benytte innsynsretten og evt klage på avslag (valgfri sak)
• Mappelevering 2: Fremskaff all informasjon du kan om en offentlig person (adresse, alder, status (CV), inntekt, eiendom, eierskapsinteresser, aksjer, verv, nettverk etc.) gjennom bruk av journalistiske metoder.
• Mappelevering 3: Finn en gravesak i pressen du mener oppfyller pressens samfunnsrolle som vaktbikkje (gruppepresentasjon på inntil 20 minutter)
• Mappelevering 4: Design et undersøkende prosjekt med en problemstilling og to hypoteser (Gruppevis).

I de praktiske oppgavene vil omfanget variere ut fra hvilke medietyper eller kombinasjoner av disse studenten velger. Omfang vil spesifiseres i oppgavetekster eller individuelt i samarbeid med faglærer. Mer informasjon om innhold og tidsfrister for oppgavene finnes i undervisningsplanen, som er elektronisk tilgjengelig for studentene ved emnestart.

Studenter som ikke leverer læringsmapper og/eller møter på gjennomganger innen gitte frister, mister retten til å få tilbakemelding.

Undervisningen foregår fysisk, på campus.

The exam in the course is an individual supervised exam of 5 hours.

No aids are permitted.

Knowledge:   

The candidate

• can classify matrices in terms of positive definiteness and eigenstructure.
• can explain the relationship between properties of a quadratic form and its defining matrix.
• can explain how Euler’s formula dictates the behaviour of solutions to differential equations.
• can explain the variational operator in contradistinction to the differential operator and establish when the use of the former is required.
• can explain the Fourier series approximation in the context of projections onto function subspaces.
• can classify a PDE and outline methods to solve it including Fourier and Laplace transforms.

Skills:   

The candidate

• can calculate the eigenstructure of a square matrix and determine diagonalizability and positive definiteness.
• can apply the Gram-Schmidt process to obtain an orthormal basis for a given inner product space.
• can apply multiple integration and vector calculus to solve relevant engineering problems.
• can solve parabolic, hyperbolic, and elliptic PDEs using the methods of Fourier or Laplace transforms where applicable.
• can apply variational calculus to derive differential equations based on the minimization of the integral form.
• can use the principle of least action to derive the Euler-Lagrange equations of mechanics.

General competence:  

The candidate

• can communicate extensive, independent work, mastering the language and terminology of engineering mathematics.
• can discuss mechanical engineering problems with peers using the terminology of engineering mathematics.
• can contribute to innovative thinking and novel solutions precipitated by applying diverse mathematical modelling paradigms and classification methods.
• can model phenomena in solid mechanics, fluid mechanics and mechatronics using the language of mathematics, in particular PDEs, variational methods and linear transformations.

Lectures and tutorials (including problem solving and the use of Python coding to solving relevant mathematical problems).

None