Programplaner og emneplaner - Student
YLEFPRA4 4. praksisperiode Emneplan
- Engelsk emnenavn
- Teaching practice, 4th period
- Studieprogram
-
Yrkesfaglærerutdanning i elektrofagYrkesfaglærerutdanning i elektrofag, nettbasertYrkesfaglærerutdanning i elektrofag, desentralisert
- Omfang
- 0.0 stp.
- Studieår
- 2021/2022
- Programplan
- Emnehistorikk
-
Innledning
Se mer utfyllende omtale av praksis i programplanen
Innhold
Admission requirements
This course is primarily aimed at PhD candidates admitted to the PhD programme in Health Sciences and PhD students from Memorial University, Newfoundland. General terms for admission to the course is a completed master's degree in molecular biology or equivalent qualification (e.g. completed MABIO4400). Priority will be given to PhD candidates from OsloMet and Memorial University, Newfoundland.
Note that all students must have a laptop not more than 2 years old (windows 7 or more recent or mac with OS X). The laptop must be able to connect to wireless network.
Arbeidskrav og obligatoriske aktiviteter
Det er krav om 100 % tilstedeværelse i pedagogisk praksis
Vurdering og eksamen
Antall dager veiledet praksis:
- 20 dager pedagogisk praksis i videregående skole
Praksis skal være veiledet og vurdert, det er praksislærer som vurderer praksis
Hvis en student ikke består en praksisperiode kan denne gjennomføres på nytt. Får studenten vurdert samme praksisperiode til ikke bestått to ganger må studiet avbrytes, jf. § 8-2 i forskrift om studier og eksamen ved OsloMet - storbyuniversitetet
Vurderingsuttrykk
The course will introduce students to basic bioinformatics including best practice when setting up and managing bioinformatics projects. The course covers introduction to high throughput sequencing technologies and will give students hands-on experience with the analysis of data from various sequencing platforms. Applications that are included in the practical part are processing of raw data reads, control of quantity and quality of data (FASTQC), expression analysis of small RNA sequencing data (miRNA) and transcriptome sequencing/microarray (mRNA-seq, cDNA) data, and detection of variation (e.g. SNPs) after resequencing (variant calling).